void CloudParticle::adapt(const CloudPFControl &controlBack, const CloudPFControl &controlNew, const bool noValidCandidates)
{
gsl_rng_env_setup();
QVec noiseT = QVec::vec3(getRandom(varianceT(0)), getRandom(varianceT(1)), getRandom(varianceT(2)));
// QVec noiseT = QVec::vec3(0,0,0);
QVec T2 = T + noiseT;
velT = T2 - T;
T = T2;
QVec noiseR = QVec::vec3(getRandom(varianceR(0)), getRandom(varianceR(1)), getRandom(varianceR(2)/10));
QVec R2 = R + noiseR;
velR = R2 - R;
R = R2;
transformation = RTMat(R(0), R(1), R(2), T);
}
void Gui::SetArm(const char* text)
{
//Initialize a surface used to hide a part of the screen wich is used later
SDL_Surface* hide = NULL;
hide=LoadImage("Images/hide.png");
//The variables that the window is going to get
double mean =0;//the mean of the arm
double variance =0;//its variance
char armType ='A';//its type
//Initializing the texts
Texts arm(0,150,_font,text,_textColor);
Texts instructions(0,250,_font2,"Choose a type of arm then click in the boxes and type the parameters",_textColor);
//Initializing the buttons
//Ok button to skip to the next window
Buttons ok(361,500, "Images/ok1.png", "Images/ok2.png","Images/ok3.png");
//Type zones for the mean and the variance
TypeZone meanT(300,400,_font2,"Mean",_textColor);
TypeZone varianceT(600,400,_font2,"Variance",_textColor);
//Radiobuttons to choose the type of arm (exponential, uniform real, uniform int, poisson, logNormal)
RadioButtons exp(100,300,"Exponential",_font2,_textColor);
RadioButtons unifr(exp.GetBox().x+exp.GetBox().w+20,300,"Uniform real",_font2,_textColor);
RadioButtons unifi(unifr.GetBox().x+unifr.GetBox().w+20,300,"Uniform int",_font2,_textColor);
RadioButtons poisson(unifi.GetBox().x+unifi.GetBox().w+20,300,"Poisson",_font2,_textColor);
RadioButtons logNormal(poisson.GetBox().x+poisson.GetBox().w+20,300,"Log-normal",_font2,_textColor);
//Calculate the x for centering them (width of the screen minus the sum the width of the buttons)
int xCentered = ((*(_screen.GetScreen())).clip_rect.w-exp.GetBox().w-unifr.GetBox().w-unifi.GetBox().w-poisson.GetBox().w-logNormal.GetBox().w-80)/2;
//Relocate the buttons
exp.SetPosition(xCentered,exp.GetBox().y);
unifr.SetPosition(exp.GetBox().x+exp.GetBox().w+20,unifr.GetBox().y);
unifi.SetPosition(unifr.GetBox().x+unifr.GetBox().w+20,unifi.GetBox().y);
poisson.SetPosition(unifi.GetBox().x+unifi.GetBox().w+20,poisson.GetBox().y);
logNormal.SetPosition(poisson.GetBox().x+poisson.GetBox().w+20,logNormal.GetBox().y);
//Display them all
arm.DisplayCentered(_screen);
instructions.DisplayCentered(_screen);
//meanT.Display(_screen);
ok.Show(_screen);
exp.Show(_screen);
unifr.Show(_screen);
unifi.Show(_screen);
poisson.Show(_screen);
logNormal.Show(_screen);
meanT.DisplayLeft(_screen,mean,_font2,_textColor);
varianceT.DisplayRight(_screen,mean,_font2,_textColor);
//Initialize the event structure
SDL_Event event;
//Initialization of the loop
bool isChoiceCorrect= false;
bool skip=false;
while((skip==false)&&(_quit==false))
{ //While there's an event to handle
while( SDL_PollEvent( &event ) )
{
//the buttons react to the user's actions
ok.HandleEvents(event);
exp.HandleEvents(event);
unifr.HandleEvents(event);
unifi.HandleEvents(event);
poisson.HandleEvents(event);
logNormal.HandleEvents(event);
meanT.HandleEvents(event,mean);
//For some button we just need the mean to set the distribution so in this case we hide the variance
if((exp.IsActive()==false)&&(poisson.IsActive()==false))
{
varianceT.HandleEvents(event,variance);
}
//we check if one option was chosen
isChoiceCorrect = (exp.IsActive()|| unifr.IsActive()||unifi.IsActive()||poisson.IsActive()||logNormal.IsActive());
//If the user clicks on ok and made a choice
if((ok.HandleEvents(event)==false)&&(isChoiceCorrect))
{
//skip to the next window
skip=true;
}
//If he clicks on ok and hasn't made a choice then change color of the text
if((ok.HandleEvents(event)==false)&&(isChoiceCorrect==false))
{
SDL_Color red={240,0,0};
exp.SetColor(red);
unifr.SetColor(red);
unifi.SetColor(red);
poisson.SetColor(red);
logNormal.SetColor(red);
}
//If the user has Xed out the window
if( event.type == SDL_QUIT )
{
//Quit the program
_quit = true;
}
}
//Display all
ok.Show(_screen);
exp.Show(_screen);
unifr.Show(_screen);
unifi.Show(_screen);
poisson.Show(_screen);
logNormal.Show(_screen);
meanT.DisplayLeft(_screen,mean, _font2,_textColor);
//For some button we just need the mean to set the distribution so in this case we hide the variance
if((exp.IsActive()==false)&&(poisson.IsActive()==false))
{
varianceT.DisplayRight(_screen,variance, _font2,_textColor);
}
else
{
ApplySurface(400,398,hide,_screen.GetScreen());
}
_screen.Display();
}
_screen.Clean("Images/background.png");
//Then we save the parameters in the Gui's attributes
//First we get the type of arm:
if(exp.IsActive()){armType='A';}
if(unifr.IsActive()){armType='B';}
if(unifi.IsActive()){armType='C';}
if(poisson.IsActive()){armType='D';}
if(logNormal.IsActive()){armType='E';}
std::vector<double> parameter;
//Then acoording to the type of arms we calculate the parameters required
switch(armType)
{
case 'A'://Exponential: we need the lambda
_choices.push_back('A');//we save the type in _choices
parameter.push_back(1.0/(mean*1.0));
_parameters.push_back(parameter);//and the parameters calculated using the mean and the variance in _parameters
break;
case 'B'://uniform real on [a,b] we need a and b
_choices.push_back('B');
parameter.push_back((2.0*mean-sqrt(12.0*variance))/2.0);
parameter.push_back((2.0*mean+sqrt(12.0*variance))/2.0);
_parameters.push_back(parameter);
break;
case 'C':
_choices.push_back('C');//uniform integer on [a,b] we need a and b
parameter.push_back((2.0*mean -sqrt(12.0*variance+1.0)+1)/2.0);
parameter.push_back((2.0*mean+sqrt(12.0*variance+1)-1)/2.0);
_parameters.push_back(parameter);
break;
case 'D': //poisson we just need the mu wich equal to the mean
_choices.push_back('D');
parameter.push_back(mean);
_parameters.push_back(parameter);
break;
default:
_choices.push_back('E'); //log-normal we need mu and sigma square
parameter.push_back(log(mean*1.0)-0.5*log(1.0+((variance*1.0)/(mean*mean*1.0))));
parameter.push_back((2.0*mean+sqrt(12.0*variance+1.0)-1.0)/2.0);
_parameters.push_back(parameter);
break;
}
}
